Test Post!
Test Post¶
Basic Markdown Functions¶
Text¶
italics
bold
~strikethrough~
blockquotes
Lists:¶
Ordered¶
- One
- Two
Unordered¶
- Cat
- Bat
Checkboxes¶
- [x] Checkboxes
- [ ] Theorem environments
(For some reason, as of the time of writing the checkboxes also have bullets beside them, which is not desired.)
Unicode text¶
μῆνιν ἄειδε θεὰ Πηληϊάδεω Ἀχιλῆος
οὐλομένην, ἣ μυρί᾽ Ἀχαιοῖς ἄλγε᾽ ἔθηκε,
πολλὰς δ᾽ ἰφθίμους ψυχὰς Ἄϊδι προΐαψεν
ἡρώων, αὐτοὺς δὲ ἑλώρια τεῦχε κύνεσσιν
5οἰωνοῖσί τε πᾶσι, Διὸς δ᾽ ἐτελείετο βουλή,
ἐξ οὗ δὴ τὰ πρῶτα διαστήτην ἐρίσαντε
Ἀτρεΐδης τε ἄναξ ἀνδρῶν καὶ δῖος Ἀχιλλεύς.
Images from the web¶

Mathematics¶
The flavor of Markdown I'm using supports $\LaTeX$ typesetting of mathematics via MathJax.
For instance, here are Maxwell's equations:
\begin{align} \nabla \times \vec{\mathbf{B}} -\, \frac1c\, \frac{\partial\vec{\mathbf{E}}}{\partial t} & = \frac{4\pi}{c}\vec{\mathbf{j}} \\ \nabla \cdot \vec{\mathbf{E}} & = 4 \pi \rho \\ \nabla \times \vec{\mathbf{E}}\, +\, \frac1c\, \frac{\partial\vec{\mathbf{B}}}{\partial t} & = \vec{\mathbf{0}} \\ \nabla \cdot \vec{\mathbf{B}} & = 0 \end{align}It doesn't seem to support theorem environments, alas.
Python code¶
# a comment
import pandas as pd
import numpy as np
import plotly.express as px
import plotly.graph_objects as go
from urllib.request import urlopen
import json
Data frames¶
df = px.data.iris()
df
# example graph using the Iris dataset
df = px.data.iris()
fig = px.scatter(df, x="sepal_width", y="sepal_length", color="species", marginal_y="violin",
marginal_x="box", trendline="ols", template="simple_white")
fig.show()
Scatterplots¶
# the same dataset in 3d
fig = px.scatter_3d(df, x='sepal_length', y='sepal_width', z='petal_width',
color='species')
fig.show()
Area charts¶
Another example visualizing topographical data with a color scheme.
# 3D surface example plot from the plotly docs
# Read data from a csv
z_data = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/api_docs/mt_bruno_elevation.csv')
fig = go.Figure(data=[go.Surface(z=z_data.values)])
fig.update_layout(title='Mt Bruno Elevation', autosize=False,
width=500, height=500,
margin=dict(l=65, r=50, b=65, t=90))
fig.show()
Geodata visualizations¶
Another cool chloropleth example from the docs that utilizes GeoJSON to visualize the unemployment rate in the US by county.
with urlopen('https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json') as response:
counties = json.load(response)
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv",
dtype={"fips": str})
fig = px.choropleth_mapbox(df, geojson=counties, locations='fips', color='unemp',
color_continuous_scale="Viridis",
range_color=(0, 12),
mapbox_style="carto-positron",
zoom=3, center = {"lat": 37.0902, "lon": -95.7129},
opacity=0.5,
labels={'unemp':'unemployment rate'}
)
fig.update_layout(margin={"r":0,"t":0,"l":0,"b":0})
fig.show()